2019 International Conference on Asian Language Processing (IALP)最新文献_第8页

Examination-Style Reading Comprehension with Neural augmented Retrieval 基于神经增强检索的考试式阅读理解

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037657

Yiqing Zhang, Hai Zhao, Zhuosheng Zhang

引用次数: 1

Towards Robust Neural Machine Reading Comprehension via Question Paraphrases 基于问题释义的鲁棒神经机器阅读理解

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037673

Ying Li, Hongyu Li, Jing Liu

{"title":"Towards Robust Neural Machine Reading Comprehension via Question Paraphrases","authors":"Ying Li, Hongyu Li, Jing Liu","doi":"10.1109/IALP48816.2019.9037673","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037673","url":null,"abstract":"In this paper, we focus on addressing the over-sensitivity issue of neural machine reading comprehension (MRC) models. By oversensitivity, we mean that the neural MRC models give different answers to question paraphrases that are semantically equivalent. To address this issue, we first create a large-scale Chinese MRC dataset with high-quality question paraphrases generated by a toolkit used in Baidu Search. Then, we quantitively analyze the oversensitivity issue of the neural MRC models on the dataset. Intuitively, if two questions are paraphrases of each other, a robust model should give the same predictions. Based on this intuition, we propose a regularized BERT-based model to encourage the model give the same predictions to similar inputs by leveraging high-quality question paraphrases. The experimental results show that our approaches can significantly improve the robustness of a strong BERT-based MRC model and achieve improvements over the BERT-based model in terms of held-out accuracy. Specifically, the different prediction ratio (DPR) for question paraphrases of the proposed model decreases more than 10%.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Are Scoring Feedback of CAPT Systems Helpful for Pronunciation Correction? –An Exception of Mandarin Nasal Finals CAPT系统的评分反馈对发音纠正有帮助吗?——普通话鼻音韵母的一个例外

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037720

Rui Cai, Wei Wei, Jinsong Zhang

{"title":"Are Scoring Feedback of CAPT Systems Helpful for Pronunciation Correction? –An Exception of Mandarin Nasal Finals","authors":"Rui Cai, Wei Wei, Jinsong Zhang","doi":"10.1109/IALP48816.2019.9037720","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037720","url":null,"abstract":"The scoring feedback of Computer Assisted Pronunciation Training (CAPT) systems facilitate learner’s instant awareness of their problems, easily lead to more practices. But whether it is enough to instruct the learners to understand how to correct their errors is still unknown. To see in depth, the impacts from CAPT technology on language learning, and to investigate learner’s correction strategy after receiving error warnings, this paper studies long term learning data of Chinese utterances by a number of CSL (Chinese as a Second Language) learners, with special efforts paid to the utterances of nasal Finals. The data resulted from a 3-week use of a CAPT APP, called “SAIT汉语” for Chinese learning, by 10 learners with different mother tongues. Major findings include: 1) Improvements were seen with almost all kinds of phonemes, except nasal Finals; 2) Data analyses showed that the learners had tried to lengthen the nasal codas after they received error warnings, while Chinese native data shows a significant nasalization period before a short coda. These results suggest that the scoring feedback can be beneficial to pronunciation training in most cases, except for some special ones. For the sounds such as Chinese nasal Finals, more appropriate feedback method is desired.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131242648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Statistical Analysis of Syllable Duration of Uyghur Language 维吾尔语音节音长的统计分析

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037656

A. Hamdulla, Guzalnur Dilmurat, Gulnur Arkin, Mijit Ablimit

引用次数: 1

Converting an Indonesian Constituency Treebank to the Penn Treebank Format 将印尼选区树库转换为宾州树库格式

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037723

Jessica Naraiswari Arwidarasti, Ika Alfina, A. Krisnadhi

引用次数: 5

Exploring Characteristics of Word Co-occurrence Network in Translated Chinese 翻译汉语词共现网络特征探析

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037722

Jianyu Zheng, Kun Ma, Xuemei Tang, Shichen Liang

{"title":"Exploring Characteristics of Word Co-occurrence Network in Translated Chinese","authors":"Jianyu Zheng, Kun Ma, Xuemei Tang, Shichen Liang","doi":"10.1109/IALP48816.2019.9037722","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037722","url":null,"abstract":"The translation activity involves both the source language and the target language. Compared to the standard texts in the two language, translated texts show unique language characteristics. In order to explore them from the perspective of integrality and complexity, we introduce complex network method into the study on translated Chinese. Firstly, selected the experimental texts from The ZJU Corpus of Translational Chinese (ZCTC) and its corresponding six sub-corpora, such as Press reportage and Popular lore. And then removed the punctuation and did word segmentation. Secondly, constructed a word co-occurrence network of translated Chinese. After analyzing and counting the parameters, such as their shortest path lengths, degree distributions and clustering coefficients in these networks, we verify that the word co-occurrence network of translated Chinese has small world effect and scale-free property. Finally, by constructing co-occurrence networks of standard Chinese and calculating their network parameters, we compare and verify the differences between translated Chinese and standard Chinese: “simplification” and the more usage of common words. Our work expands the application of complex network in translation studies, and provides a feasible approach for studying translated Chinese based on complex networks.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122576708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Syntax-aware Transformer Encoder for Neural Machine Translation 用于神经机器翻译的语法感知转换器编码器

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037672

Sufeng Duan, Hai Zhao, Junru Zhou, Rui Wang

引用次数: 14

Using WHY-type Question-Answer Pairs to Improve Implicit Causal Relation Recognition 利用“为什么”型问答对改进内隐因果关系识别

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037693

Huibin Ruan, Yu Hong, Yu Sun, Yang Xu, Min Zhang

{"title":"Using WHY-type Question-Answer Pairs to Improve Implicit Causal Relation Recognition","authors":"Huibin Ruan, Yu Hong, Yu Sun, Yang Xu, Min Zhang","doi":"10.1109/IALP48816.2019.9037693","DOIUrl":"https://doi.org/10.1109/IALP48816.2019.9037693","url":null,"abstract":"Implicit causal relation recognition aims to identify the causal relation between a pair of arguments. It is a challenging task due to the lack of conjunctions and the shortage of labeled data. In order to improve the identification performance, we come up with an approach to expand the training dataset. On the basis of the hypothesis that there inherently exists causal relations in WHY-type Question-Answer (QA) pairs, we utilize WHY-type QA pairs for the training set expansion. In practice, we first collect WHY-type QA pairs from the Knowledge Bases (KBs) of the reading comprehension tasks, and then convert them into narrative argument pairs by Question-Statement Conversion (QSC). In order to alleviate redundancy, we use active learning (AL) to select informative samples from the synthetic argument pairs. The sampled synthetic argument pairs are added to the Penn Discourse Treebank (PDTB), and the expanded PDTB is used to retrain the neural network-based classifiers. Experiments show that our method yields a performance gain of 2.42% F 1-score when AL is used, and 1.61% without using.","PeriodicalId":208066,"journal":{"name":"2019 International Conference on Asian Language Processing (IALP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120807035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Development of a Filipino Speaker Diarization in Meeting Room Conversations 菲律宾语在会议室对话中的发展

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037733

Angelica H. De La Cruz, Rodolfo C. Raga

引用次数: 0

Research on Tibetan Text Classification Method Based on Neural Network 基于神经网络的藏文文本分类方法研究

2019 International Conference on Asian Language Processing (IALP) Pub Date : 2019-11-01 DOI: 10.1109/IALP48816.2019.9037706

Zhensong Li, Jie Zhu, Zhixiang Luo, Saihu Liu

引用次数: 1